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An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback

Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system’s metabolome. This allows the recognition...

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Autores principales: Lebeau-Roche, Emmanuelle, Daniele, Gaëlle, Fildier, Aurélie, Turies, Cyril, Dedourge-Geffard, Odile, Porcher, Jean-Marc, Geffard, Alain, Vulliet, Emmanuelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8629232/
https://www.ncbi.nlm.nih.gov/pubmed/34843526
http://dx.doi.org/10.1371/journal.pone.0260354
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author Lebeau-Roche, Emmanuelle
Daniele, Gaëlle
Fildier, Aurélie
Turies, Cyril
Dedourge-Geffard, Odile
Porcher, Jean-Marc
Geffard, Alain
Vulliet, Emmanuelle
author_facet Lebeau-Roche, Emmanuelle
Daniele, Gaëlle
Fildier, Aurélie
Turies, Cyril
Dedourge-Geffard, Odile
Porcher, Jean-Marc
Geffard, Alain
Vulliet, Emmanuelle
author_sort Lebeau-Roche, Emmanuelle
collection PubMed
description Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system’s metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies.
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spelling pubmed-86292322021-11-30 An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback Lebeau-Roche, Emmanuelle Daniele, Gaëlle Fildier, Aurélie Turies, Cyril Dedourge-Geffard, Odile Porcher, Jean-Marc Geffard, Alain Vulliet, Emmanuelle PLoS One Research Article Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system’s metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies. Public Library of Science 2021-11-29 /pmc/articles/PMC8629232/ /pubmed/34843526 http://dx.doi.org/10.1371/journal.pone.0260354 Text en © 2021 Lebeau-Roche et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lebeau-Roche, Emmanuelle
Daniele, Gaëlle
Fildier, Aurélie
Turies, Cyril
Dedourge-Geffard, Odile
Porcher, Jean-Marc
Geffard, Alain
Vulliet, Emmanuelle
An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title_full An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title_fullStr An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title_full_unstemmed An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title_short An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
title_sort optimized lc-hrms untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8629232/
https://www.ncbi.nlm.nih.gov/pubmed/34843526
http://dx.doi.org/10.1371/journal.pone.0260354
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